Intermediate

AI-Assisted Investigation

Accelerate security investigations with AI-powered enrichment, entity profiling, automated evidence collection, and intelligent root cause analysis.

Automated Enrichment Pipeline

When an alert is triaged for investigation, AI automatically gathers context from multiple sources:

  1. IOC Enrichment

    Automatically look up IP reputation, domain WHOIS, file hash analysis, and threat intelligence matches for all indicators in the alert.

  2. Entity Context

    Pull the user's role, recent activity history, device inventory, access permissions, and HR status (e.g., departing employee).

  3. Historical Correlation

    Search for similar past incidents involving the same entities, techniques, or indicators to provide investigative precedent.

  4. Impact Scoping

    Identify all systems and data stores the affected entity has accessed recently to estimate potential blast radius.

AI Investigation Copilot

CapabilityHow It HelpsTime Saved
Natural Language QueriesAsk questions about the incident in plain English instead of writing complex queries5-10 min per query
Next Step SuggestionsAI recommends investigation steps based on similar past incidents and current evidence15-30 min per case
Report GenerationAutomatically draft investigation reports from case data and analyst notes30-60 min per report
Evidence SummarizationSummarize large volumes of log data and intelligence into key findings20-40 min per case
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Investigation Tip: Use AI to build entity timelines that visualize all activities by a user or host across all log sources on a single timeline. This reveals attack progression patterns that are hard to spot in individual log searches.

Root Cause Analysis

Attack Graph Analysis

AI constructs and traverses attack graphs to trace the path from initial compromise to current alert, identifying the root cause.

Causal Inference

Statistical models determine which events caused which outcomes, distinguishing correlation from causation in complex incidents.

Scope Determination

ML models estimate the full scope of compromise by analyzing communication patterns and lateral movement indicators.

Remediation Mapping

AI maps root causes to specific remediation actions, ensuring the underlying vulnerability is addressed, not just the symptoms.

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Looking Ahead: In the next lesson, we will explore response automation, including AI-driven containment, remediation, and human-in-the-loop workflows.